Comparison of Open Access Global DEMs for Geomorphological Applications in Coastal Areas Using LiDAR Data

Digital Elevation Models (DEMs) are essential tools for terrain analysis. However, their selection often focuses on spatial resolution or overall vertical accuracy, overlooking aspects such as geometric consistency or fitness for specific applications. This misalignment between DEM’s capabilities and study requirements can lead to inaccurate interpretations, undermining the reliability of the results. To address this, we assessed the accuracy of seven freely available global DEMs (SRTM, ASTER, ALOS, Copernicus DEM, MERIT DEM, NASADEM, and FABDEM) against a 1 m LiDAR reference in a coastal region of El Salvador. Our workflow combined traditional metrics (RMSE, MAE, ME) with spatial error visualizations (histograms and heatmaps) and introduced the Spatial Error Robustness Index (SERI) with RMSE/SD ratio to jointly quantify error magnitude and variability. Elevation and slope were selected for DEM–LiDAR comparisons. Results show that all DEMs systematically overestimate elevation, with slope errors amplified by scale discrepancies. FABDEM achieved the highest elevation accuracy across coastal and tectonic landscapes, ALOS the lowest slope RMSE overall and Copernicus performed best in coastal zones; DEM performance depends on terrain and parameters. The SERI and RMSE/SD ratio, combined with spatial visualizations, revealed systematic error patterns and improved geomorphic coherence interpretation.